Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Jurnal Sistem Cerdas
Salma, Farah Sherina
Unknown Affiliation
Automotive Engineering Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Classification of High School History Questions Based on Cognitive Level Revised Bloom's Taxonomy Using K-Nearest Neighbor Method Salma, Farah Sherina; Pratiwi, Oktariani Nurul; Fa’rifah, Riska Yanu
Jurnal Sistem Cerdas Vol. 8 No. 2 (2025)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v8i2.254

Abstract

Education plays an important role in transmitting knowledge to its students and to measure how well the student understands, testing is needed based on the cognitive level of knowledge. In measuring the cognitive level, it can be applied with reference to the Revised Bloom's Taxonomy which explains the regulation of learning processes and targets. Then by testing knowledge through the questions that have been made, it is necessary to classify the questions into several cognitive levels according to Revised Bloom's Taxonomy to determine the learning process and understanding of each individual. Many types of questions that are formed make classification difficult because the method is still done manually, therefore machine learning is needed. This study will focus on the classification of questions from the History subject in high school. The dataset used is downloaded from internet searches of USBN, PAS, PTS, and other exams. This study focuses on RBT C4 to C6 only. This study uses the K-Nearest Neighbor algorithm to obtain accuracy and with the imbalance of data in the dataset, an oversampling method using SMOTE will also be used. The accuracy results obtained are precision is 76%, recall is 76%, f1-score is 74%, accuracy is 76%. Keywords—question classification, KNN, high school history, SMOTE, RBT, oversampling
Co-Authors Fa'rifah, Riska Yanu Oktariani Nurul Pratiwi